Particle Filter Based State Estimation of Power System
Dipesh Shirishbhai Doshi, Mukul Chankaya · 2017
State estimation is very important for the analysis of power system. It helps for controlling and monitoring of the power system. With the help of it optimal state of the power system can be obtained. It measures the voltage and current phasors and also measure the angles between buses. So estimation of the power system should be more accurate. Power system is highly non-linear so it is not an easy task to forecast the state of the power system with the methods used before. Particle filter is very obvious solution for these type of non-linear system. It gives very accurate results of the estimations of the system. RMS error due to particle filter between actual and estimated state of the system is very low in compare to conventional estimators. Here for the estimation purpose we have used data of the six bus system and tried to estimate the voltage for the bus number one.